Identifying multiple sclerosis in women of childbearing age in six European countries: a contribution from the ConcePTION project.

IF 5.9 1区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Marie Beslay,Yvonne Geissbühler,Anna-Belle Beau,Davide Messina,Justine Benevent,Elisa Ballardini,Laia Barrachina-Bonet,Clara Cavero-Carbonell,Alex Coldea,Laura García-Villodre,Anja Geldhof,Rosa Gini,Kerstin Hellwig,Sue Jordan,Maarit K Leinonen,Sandra Lopez-Leon,Marco Manfrini,Visa Martikainen,Vera R Mitter,Amanda J Neville,Hedvig Nordeng,Aurora Puccini,Sandra Vukusic,Joan K Morris,Christine Damase-Michel
{"title":"Identifying multiple sclerosis in women of childbearing age in six European countries: a contribution from the ConcePTION project.","authors":"Marie Beslay,Yvonne Geissbühler,Anna-Belle Beau,Davide Messina,Justine Benevent,Elisa Ballardini,Laia Barrachina-Bonet,Clara Cavero-Carbonell,Alex Coldea,Laura García-Villodre,Anja Geldhof,Rosa Gini,Kerstin Hellwig,Sue Jordan,Maarit K Leinonen,Sandra Lopez-Leon,Marco Manfrini,Visa Martikainen,Vera R Mitter,Amanda J Neville,Hedvig Nordeng,Aurora Puccini,Sandra Vukusic,Joan K Morris,Christine Damase-Michel","doi":"10.1007/s10654-025-01264-3","DOIUrl":null,"url":null,"abstract":"Prevalence of Multiple Sclerosis (MS) has increased over the last decades, primarily among women of childbearing age. Several algorithms for identifying MS have been described in the literature, providing heterogeneous prevalence estimates. We compared five algorithms to identify MS in women of childbearing age and estimated MS prevalence by time period and age-group. The study population included women aged 15 to 49 years-old between 2005 and 2019, from three data sources including all women (from Italy, Norway, and Wales), and three including pregnant women only (from France, Finland, and Spain; data collected around pregnancy). Five algorithms were tested: MS1 to MS3 combined MS diagnoses and MS-medicine prescriptions/dispensations, requiring 1, 2, or 3 occurrences, respectively; MS4 and MS5 used only MS diagnoses, requiring at least 2 occurrences (MS4 allowed just 1 if diagnosis was from inpatient care). In 2015-2019, MS prevalence based on MS1 ranged from 109 to 359 per 100,000 women: 109 in France, 121 in Spain, 195 in Wales, 232 in Finland, 264 in Italy, and 359 in Norway. More restrictive algorithms led to greater disparity, with MS3 ranging from 53 in Spain to 325 in Norway, and MS5 from 21 in France to 345 in Norway. All algorithms showed expected prevalence trends by time and age among women of childbearing age, though lower than in the literature. Overall, MS1 provided prevalence estimates most closely aligned with existing literature. This study offers key insights into choosing algorithms for identifying MS in women of childbearing age and in pregnant women.","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"30 1","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10654-025-01264-3","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

Abstract

Prevalence of Multiple Sclerosis (MS) has increased over the last decades, primarily among women of childbearing age. Several algorithms for identifying MS have been described in the literature, providing heterogeneous prevalence estimates. We compared five algorithms to identify MS in women of childbearing age and estimated MS prevalence by time period and age-group. The study population included women aged 15 to 49 years-old between 2005 and 2019, from three data sources including all women (from Italy, Norway, and Wales), and three including pregnant women only (from France, Finland, and Spain; data collected around pregnancy). Five algorithms were tested: MS1 to MS3 combined MS diagnoses and MS-medicine prescriptions/dispensations, requiring 1, 2, or 3 occurrences, respectively; MS4 and MS5 used only MS diagnoses, requiring at least 2 occurrences (MS4 allowed just 1 if diagnosis was from inpatient care). In 2015-2019, MS prevalence based on MS1 ranged from 109 to 359 per 100,000 women: 109 in France, 121 in Spain, 195 in Wales, 232 in Finland, 264 in Italy, and 359 in Norway. More restrictive algorithms led to greater disparity, with MS3 ranging from 53 in Spain to 325 in Norway, and MS5 from 21 in France to 345 in Norway. All algorithms showed expected prevalence trends by time and age among women of childbearing age, though lower than in the literature. Overall, MS1 provided prevalence estimates most closely aligned with existing literature. This study offers key insights into choosing algorithms for identifying MS in women of childbearing age and in pregnant women.
确定六个欧洲国家育龄妇女多发性硬化症:来自ConcePTION项目的贡献。
在过去的几十年里,多发性硬化症(MS)的患病率增加了,主要是在育龄妇女中。文献中描述了几种识别多发性硬化症的算法,提供了异质患病率估计。我们比较了五种识别育龄妇女多发性硬化症的算法,并按时间段和年龄组估计多发性硬化症的患病率。研究人群包括2005年至2019年期间15至49岁的女性,来自三个数据来源,包括所有女性(来自意大利、挪威和威尔士),三个数据来源仅包括孕妇(来自法国、芬兰和西班牙;数据收集于怀孕前后)。测试了五种算法:MS1至MS3合并MS诊断和MS药物处方/配剂,分别需要1、2或3次出现;MS4和MS5只使用多发性硬化症诊断,至少需要2次(MS4只允许1次,如果诊断来自住院治疗)。2015-2019年,基于MS1的MS患病率为每10万名女性109至359人:法国109人,西班牙121人,威尔士195人,芬兰232人,意大利264人,挪威359人。更严格的算法导致了更大的差异,MS3从西班牙的53到挪威的325,MS5从法国的21到挪威的345。所有算法都显示了育龄妇女按时间和年龄的预期流行趋势,尽管低于文献。总体而言,MS1提供的患病率估计与现有文献最接近。这项研究为选择识别育龄妇女和孕妇多发性硬化症的算法提供了关键见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
European Journal of Epidemiology
European Journal of Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
21.40
自引率
1.50%
发文量
109
审稿时长
6-12 weeks
期刊介绍: The European Journal of Epidemiology, established in 1985, is a peer-reviewed publication that provides a platform for discussions on epidemiology in its broadest sense. It covers various aspects of epidemiologic research and statistical methods. The journal facilitates communication between researchers, educators, and practitioners in epidemiology, including those in clinical and community medicine. Contributions from diverse fields such as public health, preventive medicine, clinical medicine, health economics, and computational biology and data science, in relation to health and disease, are encouraged. While accepting submissions from all over the world, the journal particularly emphasizes European topics relevant to epidemiology. The published articles consist of empirical research findings, developments in methodology, and opinion pieces.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信